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Automatic Diagnosis

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Color Atlas of Melanocytic Lesions of the Skin

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Abstract

Diagnosis of melanocytic skin tumours is traditionally based on the subject of evaluation of images by an expert in the discipline. Despite increasing refinement of subjective criteria – introducing some degree of “objectivity” – there is a continuous demand for truly objective diagnostic features. This means features independent of the subjective judgement of a human observer, or, more drastically, features created and interpreted by a machine.

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Literatur

  • (2005) Possible histopathologic correlates of dermoscopic features in pigmented melanocytic lesions identified by means of optical coherence tomography. Exp Dermatol 14: 56–59

    Google Scholar 

  • Chang Y, Stanley RJ, Moss RH, Van Stoecker W (2005) A systematic heuristic approach for feature selection for melanoma discrimination using clinical images. Skin Res Technol 11: 165–178

    Article  PubMed  Google Scholar 

  • Chen J, Stanley RJ, Moss RH, Van Stoecker W (2003) Colour analysis of skin lesion regions from melanoma discrimination in clinical images. Skin Res Technol 9: 94–104

    Article  PubMed  Google Scholar 

  • Farkas DL, Becker D (2001) Applications of spectral imaging: detection and analysis of human melanoma and its precursors. Pigment Cell Res 14: 2–8

    Article  PubMed  CAS  Google Scholar 

  • Gerger A, Koller S, Weger W, Richtig E, Kerl H, Samonigg H, Krippl P, Smolle J (2006) Sensitivity and specificity of confocal laser-scanning microscopy for in vivo diagnosis of malignant skin tumors. Cancer 107: 193–200

    Article  PubMed  Google Scholar 

  • Gerger A, Stolz W, Pompl R, Smolle J (2003) Automated epiluminescence microscopy-tissue counter analysis using CAR T and 1-NN in the diagnosis of melanoma. Skin Res Technol 9: 105–110

    Article  PubMed  Google Scholar 

  • Gniadecka M, Philipsen PA, Sigurdsson S, Wessel S, Nielsen OF, Christensen DH, Hercogova J, Rossen K, Thomsen HK, Gniadecki R, Hansen LK, Wulf HC (2004) Melanoma diagnosis by Raman spectroscopy and neural networks: structure alterations in proteins and lipids in intact cancer tissue. J Invest Dermatol 122: 443–449

    Article  PubMed  CAS  Google Scholar 

  • Gruber MJ, Wackernagel A, Richtig E, Koller S, Kerl H, Smolle J (2005) Digital image enhancement for in vivo laser scanning microscopy. Skin Res Technol 11: 248–253

    Article  PubMed  Google Scholar 

  • Guillard G, Lagarde JM (2005) Skin lesions segmentation and quantification from 3D body's models. Skin Res Technol 11: 123–131

    Article  PubMed  CAS  Google Scholar 

  • Haenssle HA, Krueger U, Vente C, Thoms K-M, Bertsch HP, Zutt M, Rosenberger A, Neumann C, Emmert S (2006) Results from an observational trial: digital epiluminescence microscopy followup of atypical Nevi increases the sensitivity and the chance of success of conventional dermoscopy in detecting melanoma. J Invest Dermatol 126: 980–985

    Article  PubMed  CAS  Google Scholar 

  • Har-Shai Y, Glickman Y, Siller G, McLeod R, Topaz M, Howe C, Ginzburg A, Zamir B, Filo OP, Kenan GP, Ullmann Y (2005) Electrical impedance scanning for melanoma diagnosis: a validation study. Plast Reconstr Surg 116: 782–790

    Article  PubMed  CAS  Google Scholar 

  • Hartmann P, Ziegler W, Lübbers DW (1996) Fluorescence life time imaging of the skin pO2: instrumentation and results. Adv Exp Med Biol 428: 605–611

    Google Scholar 

  • Kahofer P, Hofmann-Wellenhof R, Smolle J (2002) Tissue counter analysis of dermatoscopic images of melanocytic skin tumors: preliminary findings. Melanoma Res 12: 71–75

    Article  PubMed  CAS  Google Scholar 

  • Kittler H, Guitera P, Riedl E, Avramidis M, Teban L, Fiebiger M, Weger RA , Dawid M, Menzies S (2006) Identification of clinically featureless incipient melanoma using sequential dermoscopy imaging. Arch Dermatol 142: 1113–1119

    Article  PubMed  Google Scholar 

  • Manousaki AG, Manios AG, Tsompanaki EI, Panayiotides JG, Tsiftsis DD, Kostaki AK, Tosca AD (2006) A simple digital image processing system to aid in melanoma diagnosis in an everyday melanocytic skin lesion unit. A preliminary report . Int J Dermatol 45: 402–410

    Article  PubMed  Google Scholar 

  • Moncrieff M, Cotton S, Claridge E, Hall P (2002) Spetrophotometric intracutaneous analysis: a new technique for imaging pigmented skin lesions. Br J Dermatol 146: 448–457

    Article  PubMed  CAS  Google Scholar 

  • Muryph BW, Webster RJ, Turlach BA, Quirk CJ, Clay CD, Heenan PJ, Sampson DD (2005) Towards the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy. J Biomed Optics 10:064020

    Article  Google Scholar 

  • O ka H, Iyatomi H, Hashimoto M, Tanaka M (2006) Reply to “Digital dermoscopy analysis and internetbased program for discrimination of pigmented skin lesion dermoscopic images”. Br J Dermatol 154: 570–571

    Article  Google Scholar 

  • O no I, Sakemoto A, Ogino J, Kamyia T, Yamashita T, Jimbow K (2006) The real-time, three-dimensional analyses of benign and malignant skin tumors by confocal laser scanning microscopy. J Dermatol Sci 43: 135–141

    Article  Google Scholar 

  • R allan D, Dickson M, Busch NL, Harland CC, Mortimer P, Bamber JC (2006) High-resolution ultrasound reflex transmission imaging and digital photgraphy: potential tools for the quantitative assessment of pigmented lesions. Skin Res Technol 12:50–59

    Article  Google Scholar 

  • R allan D, Bush NL, Bamber JC, Harland CC (2006) Quantitative discrimination of pigmented lesions using three-dimensional high-resolution ultrasound reflex transmission imaging. J Invest Dermatol 127: 189–195

    Google Scholar 

  • R osado B, Menzies S, Harbauer A, Pehamberger H, Wolff K, Binder M, Kittler H (2003) Accuracy of computer diagnosis of melanoma. A quantitative meta-analysis. Arch Dermatol 139: 361–367

    Article  Google Scholar 

  • R ubegni P, Burroni M, Sbano P, Andreassi L (2005) Digital dermoscopy analysis and Internet-based program for discrimination of pigmented skin lesion dermoscopic images. Br J Dermatol 152: 395–396

    Article  Google Scholar 

  • Salmhofer W, Rieger E, Soyer HP, Smolle J, Kerl H (1996) Influence of skin tension and formalin fixation on sonographic measurement of tumor thickness. J Am Acad Dermatol 34: 34–39

    Article  PubMed  CAS  Google Scholar 

  • Seidenari S, Pellacani G, Grana C (2005) Pigment distribution in melanocytic lesion images: a digital parameter to be employed for computer-aided diagnosis. Skin Res Technol 11: 236–241

    Article  PubMed  CAS  Google Scholar 

  • She Z, Fish PJ (2003) Analysis of skin line pattern for lesion classification. Skin Res Technol 9: 73–80

    Article  PubMed  Google Scholar 

  • Smolle J (2000) Diagnostic assessment of cutaneous melanoma and common nevi using tissue counter analysis. Analyt Quant Cytol Histol 22: 299–306

    CAS  Google Scholar 

  • Stoecker VW, Gupta K, Stanley RJ, Moss RH, Shrestha B (2005) Detection of asymmetric blotches (asymmetric structureless areas) in dermoscopy images of malignant melanoma using relative color. Skin Res Technol 11: 179–184

    Article  PubMed  Google Scholar 

  • Stücker M, Springer C, Paech V, Hermes N, Hoffmann M, Altmeyer P (2006) Increased laser Doppler flow in skin tumors corresponds to elevated vessel density and reactive hyperemia. Skin Res Technol 12: 1–6

    Article  PubMed  Google Scholar 

  • Wiltgen M, Gerger A, Wagner C, Bergthaler P, Smolle J (2004) Evaluation of the influence of image compression on the automatic discrimination of histological images of skin lesions. Meth Inform Med 43: 141–149

    PubMed  CAS  Google Scholar 

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Editor information

Editors and Affiliations

  1. The Queensland Institute of Dermatology, University of Queensland, QLD 4102, Brisbane, Australia

    Hans Peter Soyer

  2. Department of Dermatology, Second University of Naples, Via Pansini 5, I-80131, Naples, Italy

    Guiseppe Argenziano

  3. Department of Dermatology, Medical University Graz, Auenbruggerplatz 8, A-8036, Graz, Austria

    Rainer Hofmann-Wellenhof

  4. Pigmented Lesion Clinic, University of Miami, School of Medicine, 33136, Miami, FL, USA

    Robert H. Johr

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© 2007 Springer-Verlag Berlin Heidelberg

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(2007). Automatic Diagnosis. In: Soyer, H., Argenziano, G., Hofmann-Wellenhof, R., Johr, R. (eds) Color Atlas of Melanocytic Lesions of the Skin. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-35106-1_6

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  • DOI: https://doi.org/10.1007/978-3-540-35106-1_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-35105-4

  • Online ISBN: 978-3-540-35106-1

  • eBook Packages: MedicineMedicine (R0)

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